We propose a belief propagation list (BPL) decoder with comparable
performance to the successive cancellation list (SCL) decoder of polar codes,
which already achieves the maximum likelihood (ML) bound of polar codes for
sufficiently large list size $L$. The proposed decoder is composed of multiple
parallel independent belief propagation (BP) decoders based on differently
permuted polar code factor graphs. A list of possible transmitted codewords is
generated and the one closest to the received vector, in terms of Euclidean
distance, is picked. To the best of our knowledge, the proposed BPL decoder
provides the best performance of plain polar codes under iterative decoding
known so far. The proposed algorithm does not require any changes in the polar
code structure itself, rendering the BPL into an alternative to the SCL
decoder, equipped with a soft output capability enabling, e.g., iterative
detection and decoding to further improve performance. Further benefits are
lower decoding latency compared to the SCL decoder and the possibility of high
throughput implementations. Additionally, we show that a different selection
strategy of frozen bit positions can further enhance the error-rate performance
of the proposed decoder.

本文提出了一种基于置信传播列表（BPL）的解码器，实现了与连续取消列表（SCL）解码器相当的性能，并且没有改变极化码的结构，是连续取消列表（SCL）解码器的一种替代方案，可用于迭代检测和译码以进一步提高性能。此外，该算法具有较低的解码延迟和高吞吐量实现的可能性，并且可以通过不同的选位冻结策略进一步增强误码率性能。